Cargando…

Comprehensive landscape of TGFβ-related signature in osteosarcoma for predicting prognosis, immune characteristics, and therapeutic response

Osteosarcoma (OS) is a highly heterogeneous malignant bone tumor, and its tendency to metastasize leads to a poor prognosis. TGFβ is an important regulator in the tumor microenvironment and is closely associated with the progression of various types of cancer. However, the role of TGFβ-related genes...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Dong, Peng, Ye, Li, Xian, Zhu, Zhijie, Mi, Zhenzhou, Zhang, Zhao, Fan, Hongbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10205544/
https://www.ncbi.nlm.nih.gov/pubmed/37234254
http://dx.doi.org/10.1016/j.jbo.2023.100484
_version_ 1785046063680323584
author Liu, Dong
Peng, Ye
Li, Xian
Zhu, Zhijie
Mi, Zhenzhou
Zhang, Zhao
Fan, Hongbin
author_facet Liu, Dong
Peng, Ye
Li, Xian
Zhu, Zhijie
Mi, Zhenzhou
Zhang, Zhao
Fan, Hongbin
author_sort Liu, Dong
collection PubMed
description Osteosarcoma (OS) is a highly heterogeneous malignant bone tumor, and its tendency to metastasize leads to a poor prognosis. TGFβ is an important regulator in the tumor microenvironment and is closely associated with the progression of various types of cancer. However, the role of TGFβ-related genes in OS is still unclear. In this study, we identified 82 TGFβ DEGs based on RNA-seq data from the TARGET and GETx databases and classified OS patients into two TGFβ subtypes. The KM curve showed that the Cluster 2 patients had a substantially poorer prognosis than the Cluster 1 patients. Subsequently, a novel TGFβ prognostic signatures (MYC and BMP8B) were developed based on the results of univariate, LASSO, and multifactorial Cox analyses. These signatures showed robust and reliable predictive performance for the prognosis of OS in the training and validation cohorts. To predict the three-year and five-year survival rate of OS, a nomogram that integrated clinical features and risk scores was also developed. The GSEA analysis showed that the different subgroups analyzed had distinct functions, particularly, the low-risk group was associated with high immune activity and a high infiltration abundance of CD8 T cells. Moreover, our results indicated that low-risk cases had higher sensitivity to immunotherapy, while high-risk cases were more sensitive to sorafenib and axitinib. scRNA-Seq analysis further revealed that MYC and BMP8B were strongly expressed mainly in tumor stromal cells. Finally, in this study, we confirmed the expression of MYC and BMP8B by performing qPCR, WB, and IHC analyses. To conclude, we developed and validated a TGFβ-related signature to accurately predict the prognosis of OS. Our findings might contribute to personalized treatment and making better clinical decisions for OS patients.
format Online
Article
Text
id pubmed-10205544
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-102055442023-05-25 Comprehensive landscape of TGFβ-related signature in osteosarcoma for predicting prognosis, immune characteristics, and therapeutic response Liu, Dong Peng, Ye Li, Xian Zhu, Zhijie Mi, Zhenzhou Zhang, Zhao Fan, Hongbin J Bone Oncol Research Paper Osteosarcoma (OS) is a highly heterogeneous malignant bone tumor, and its tendency to metastasize leads to a poor prognosis. TGFβ is an important regulator in the tumor microenvironment and is closely associated with the progression of various types of cancer. However, the role of TGFβ-related genes in OS is still unclear. In this study, we identified 82 TGFβ DEGs based on RNA-seq data from the TARGET and GETx databases and classified OS patients into two TGFβ subtypes. The KM curve showed that the Cluster 2 patients had a substantially poorer prognosis than the Cluster 1 patients. Subsequently, a novel TGFβ prognostic signatures (MYC and BMP8B) were developed based on the results of univariate, LASSO, and multifactorial Cox analyses. These signatures showed robust and reliable predictive performance for the prognosis of OS in the training and validation cohorts. To predict the three-year and five-year survival rate of OS, a nomogram that integrated clinical features and risk scores was also developed. The GSEA analysis showed that the different subgroups analyzed had distinct functions, particularly, the low-risk group was associated with high immune activity and a high infiltration abundance of CD8 T cells. Moreover, our results indicated that low-risk cases had higher sensitivity to immunotherapy, while high-risk cases were more sensitive to sorafenib and axitinib. scRNA-Seq analysis further revealed that MYC and BMP8B were strongly expressed mainly in tumor stromal cells. Finally, in this study, we confirmed the expression of MYC and BMP8B by performing qPCR, WB, and IHC analyses. To conclude, we developed and validated a TGFβ-related signature to accurately predict the prognosis of OS. Our findings might contribute to personalized treatment and making better clinical decisions for OS patients. Elsevier 2023-05-12 /pmc/articles/PMC10205544/ /pubmed/37234254 http://dx.doi.org/10.1016/j.jbo.2023.100484 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Paper
Liu, Dong
Peng, Ye
Li, Xian
Zhu, Zhijie
Mi, Zhenzhou
Zhang, Zhao
Fan, Hongbin
Comprehensive landscape of TGFβ-related signature in osteosarcoma for predicting prognosis, immune characteristics, and therapeutic response
title Comprehensive landscape of TGFβ-related signature in osteosarcoma for predicting prognosis, immune characteristics, and therapeutic response
title_full Comprehensive landscape of TGFβ-related signature in osteosarcoma for predicting prognosis, immune characteristics, and therapeutic response
title_fullStr Comprehensive landscape of TGFβ-related signature in osteosarcoma for predicting prognosis, immune characteristics, and therapeutic response
title_full_unstemmed Comprehensive landscape of TGFβ-related signature in osteosarcoma for predicting prognosis, immune characteristics, and therapeutic response
title_short Comprehensive landscape of TGFβ-related signature in osteosarcoma for predicting prognosis, immune characteristics, and therapeutic response
title_sort comprehensive landscape of tgfβ-related signature in osteosarcoma for predicting prognosis, immune characteristics, and therapeutic response
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10205544/
https://www.ncbi.nlm.nih.gov/pubmed/37234254
http://dx.doi.org/10.1016/j.jbo.2023.100484
work_keys_str_mv AT liudong comprehensivelandscapeoftgfbrelatedsignatureinosteosarcomaforpredictingprognosisimmunecharacteristicsandtherapeuticresponse
AT pengye comprehensivelandscapeoftgfbrelatedsignatureinosteosarcomaforpredictingprognosisimmunecharacteristicsandtherapeuticresponse
AT lixian comprehensivelandscapeoftgfbrelatedsignatureinosteosarcomaforpredictingprognosisimmunecharacteristicsandtherapeuticresponse
AT zhuzhijie comprehensivelandscapeoftgfbrelatedsignatureinosteosarcomaforpredictingprognosisimmunecharacteristicsandtherapeuticresponse
AT mizhenzhou comprehensivelandscapeoftgfbrelatedsignatureinosteosarcomaforpredictingprognosisimmunecharacteristicsandtherapeuticresponse
AT zhangzhao comprehensivelandscapeoftgfbrelatedsignatureinosteosarcomaforpredictingprognosisimmunecharacteristicsandtherapeuticresponse
AT fanhongbin comprehensivelandscapeoftgfbrelatedsignatureinosteosarcomaforpredictingprognosisimmunecharacteristicsandtherapeuticresponse